A system and method for searching images by images for multi-task bayonet vehicles

A multi-task and vehicle technology, which is applied in the field of multi-task bayonet vehicle image search, can solve the problems of not reaching the level of fine-grained vehicle retrieval and not being accurate enough.

Active Publication Date: 2020-12-15
ZHEJIANG YINJIANG RES INST
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0005] "Deep Learning-Based Vehicle Vehicle Identification Model Construction Method and Vehicle Vehicle Identification Method", application number 201610962720.5, using deep learning for vehicle vehicle identification, which has not reached the level of fine-grained vehicle retrieval and is not accurate enough

Method used

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  • A system and method for searching images by images for multi-task bayonet vehicles
  • A system and method for searching images by images for multi-task bayonet vehicles
  • A system and method for searching images by images for multi-task bayonet vehicles

Examples

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Embodiment

[0106]Example: such as figure 1 As shown, a multi-tasking checkpoint vehicle image search system mainly includes four modules, namely a positioning module, a feature extraction module, an index module and an image uploading module, wherein both the positioning module and the feature extraction module include a checkpoint The treatment of the three parts of the vehicle, the annual inspection label and the headlights. The combination of the extracted feature vectors of the three parts is used as the feature vector of the bayonet vehicle. After PCA dimension reduction, the improved weighted K-means retrieval algorithm is used for retrieval, and finally the retrieved similar vehicles are uploaded.

[0107] A method for searching images by images for a multi-task bayonet vehicle, comprising the following steps:

[0108] Step 1. Data set preparation:

[0109] (1) Manually mark the vehicle, the vehicle annual inspection standard, and the area coordinate information and category of ...

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Abstract

The invention relates to a system and method for searching images by images for multi-task bayonet vehicles. The invention uses a deep neural network to establish a multi-task positioning and multi-task feature extraction network, based on an improved edge box detection technology and a cascaded loss function method Train the positioning network, respectively locate and feature detect the three parts of the vehicle in the bayonet vehicle image, the annual inspection mark and the lamp, combine the global and local features, and use the loss function of softmax loss and triple loss function to train the network , the final weighted combination of the local feature vector and the global feature vector of the last fully connected layer of the neural network is used as the vehicle feature for retrieval, and the improved k-means algorithm is used for retrieval to find out the K class, and then the SVM is used to form a hash function for Han Clear coding improves retrieval speed and saves storage space.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a system and method for searching images by images for multi-task bayonet vehicles. Background technique [0002] With the development of society, intelligent traffic monitoring in the field of intelligent transportation is a very important development direction at present. At present, a large number of electronic police and checkpoint systems have been deployed on urban roads in my country. These systems can capture high-definition pictures of vehicles in real time, and identify and analyze the license plate number, as well as some vehicle model information (such as vehicle size, color, etc.). However, in the currently used bayonet monitoring system, the license plate number recognition still has a misrecognition and missed recognition rate of about 10%. More importantly, it will not be possible to identify illegal vehicles with license plates or deliberately concealed...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/08
CPCG06N3/08G06V20/584G06F18/23213G06F18/214
Inventor 温晓岳田玉兰田彦陈涛李建元
Owner ZHEJIANG YINJIANG RES INST
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